Title :
Semantically-based 2.5D texture printing
Author :
Jianyu Wang ; Allebach, Jan P. ; Ortiz-Segovia, Maria V.
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
Relief printing, also known as 2.5D printing, is capable of representing texture in a more appealing way to the human observer due to the fact that it can reproduce the tactile details and structures of a texture. This paper describes a novel method to reproduce a given textured area of an image based on the semantic information linked to that area. A texture detector is trained offline with a non-parametric test in order to produce a printing mask which labels pixels more likely to belong to a specific texture-related semantic concept. The height map needed to print pixels in relief is calculated automatically from the printing mask and the gray-scale version of the original image.
Keywords :
image representation; image texture; statistical testing; human observer; nonparametric test; printing mask; relief printing; semantic information; semantically-based 2.5D texture printing; tactile details; texture representation; texture structure; texture-related semantic concept; Databases; Histograms; Image color analysis; Printing; Semantics; Training; Visualization; 2.5D printing; Relief printing; non-parametric test; semantic image processing; texture detection;
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
DOI :
10.1109/ICIP.2014.7025533